English-Japanese Example-Based Machine Translation Using Abstract Semantic Representations

Chris Brockett, Takako Aikawa, Anthony Aue, Arul Menezes, Chris Quirk, and Hisami Suzuki

Abstract

This presentation describes an examplebased English-Japanese machine translation system in which an abstract linguistic representation layer is used to extract and store bilingual translation knowledge, transfer patterns between languages, and generate output strings. Abstraction permits structural neutralizations that facilitate learning of translation examples across languages with radically different surface structure characteristics, and allows MT development to proceed within a largely languageindependent NLP architecture. Comparative evaluation indicates that after training in a domain the English-Japanese system is statistically indistinguishable from a non-customized commercially available MT system in the same domain.

Details

Publication typeInproceedings
URLhttp://acl.ldc.upenn.edu/coling2002/workshops/data/w07/w07-04.pdf
PublisherInternational Conference on Computational Linguistics
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